{"id":"W2295840922","doi":"","title":"IIIT Hyderabad in Summarization and Knowledge Base Population at TAC 2011","year":2011,"lang":"en","type":"article","venue":"Theory and applications of categories","topic":"Topic Modeling","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Automatic summarization; Computer science; Task (project management); Natural language processing; Population; Knowledge base; Word (group theory); Artificial intelligence; Information retrieval; Linguistics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003815281,0.0000611978,0.00008429323,0.00008099568,0.0000896405,0.00001377095,0.0001351613,0.00003601228,0.0000151785],"category_scores_gemma":[0.00001305841,0.00005908325,0.000009007734,0.0001143205,0.00006742356,0.0002523143,0.0001228796,0.00003584537,0.000004660065],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001101858,"about_ca_system_score_gemma":0.0000134963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001000706,"about_ca_topic_score_gemma":0.00006572674,"domain_scores_codex":[0.9994841,0.00005928976,0.0001577705,0.000177004,0.00004107212,0.0000807248],"domain_scores_gemma":[0.9995503,0.00007563805,0.0000597771,0.0002480831,0.00003508023,0.00003109845],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000008659041,0.00002552878,0.008736005,0.00001819212,0.000001959188,8.358395e-8,0.001827275,0.000005964702,0.0002183609,0.9660733,0.000004299794,0.02308036],"study_design_scores_gemma":[0.0001894818,0.00001786251,0.03236644,0.00000809072,0.000007306972,0.000003450882,0.0001711878,0.003778132,0.004169871,0.9588248,0.0003510008,0.0001123715],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2780756,0.0007327609,0.7159539,0.00004607681,0.00002482098,0.0002070009,0.000002075721,0.00004032485,0.004917407],"genre_scores_gemma":[0.9953412,0.00005590079,0.004173879,0.00001342354,0.00001515645,0.00005165533,0.000008266731,0.000003465994,0.0003370704],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7172656,"threshold_uncertainty_score":0.2409345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01901822072906967,"score_gpt":0.2386160547581415,"score_spread":0.2195978340290718,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}